An Image Denoising Model using Deep Learning for Digital Breast Tomosynthesis Images-Reference-Cited by-同舟云学术

An Image Denoising Model using Deep Learning for Digital Breast Tomosynthesis Images

Published:2022-07-23 Issue: Volume: Page:
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Container-title:2022 IEEE 13th Control and System Graduate Research Colloquium (ICSGRC)
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Author:

Harron Nur Athiqah¹,Osman Nadzmi Faridzuan¹,Sulaiman Siti Noraini¹,Karim Noor Khairiah A.²,Ismail Ahmad Puad¹,Soh Zainal Hisham Che¹

Affiliation:

1. Universiti Teknologi MARA,Centre for Electrical Engineering Studies,Penang,Malaysia

2. Advanced Medical and Dental Institute, Universiti Sains Malaysia Bertam,Regenerative Medicine Cluster,Penang,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9844829/9845129/09845152.pdf?arnumber=9845152

Reference15 articles.

1. FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising

2. Image Blind Denoising with Generative Adversarial Network Based Noise Modeling

3. Toward Convolutional Blind Denoising of Real Photographs

4. Deep Plug-And-Play Super-Resolution for Arbitrary Blur Kernels

5. Detection of masses and architectural distortions in digital breast tomosynthesis: A publicly available dataset of 5,060 patients and a deep learning baseline;buda;ArXiv,2020

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